Jeff M Phillips
Assistant Professor, School of Computing, University of Utah
BS Computer Science, Rice University (2003)
BA Mathematics, Rice University (2003)
Ph.D. Computer Science, Duke University (2009)
CI Postdoctoral Fellow, School of Computing, University of Utah (2009-2011)


Co-Organizer of The Data Group.
Director of Data Management and Analysis Track, part of a Big Data Program.
Member of Center for Extreme Data Management, Analysis, and Visualization.
U of Utah Address:
50 S Central Campus Dr. 3190
Salt Lake City, UT 84112
(801) 585-7775 (office)
(801) 581-5843 (fax)



Email: jeffp|at|cs.utah.edu
Office: 3442 Merril Engineering Building
CV: CV (probably out of date)


Research Interests:
Algorithms for Big Data Analytics: Geometric Data Analysis, Computational Geometry, Handling Uncertainty, Data Mining, Databases, Machine Learning, Computational Statistics.


Students:
  • Yan Zheng (PhD) started 2012
  • Mina Ghashami (PhD) started 2012
    Former Students:
  • Shashanka Krishnaswamy (MS 2013) Quality Control in Weather Updates Via Quantiles | first job @ Amazon
  • Supraja Jayakumar (MS 2013) Uncertain Centerpoints | first job @ Cerner Systems
  • Alex Clemmer (BS 2013) Streaming LDA | first jobs @ Hacker's School + Microsoft

    Teaching:
    Data Mining | CS 5140 and CS 6140 | Spring 2014 | MW 5:15-6:35pm | WEB 2230
    Data Reading Group | CS 7941 | Spring 2014 | Th 12:15-1:30pm | WEB 3147 (LCR)
    old:
    Data Mining | Spring 2013 | Spring 2012
    Data Mining Seminar | Fall 2013 (MCMD) | Fall 2012 (sampling) | Fall 2010 (uncertainty)
    Data Group | Spring 2012
    Models of Computation for Massive Data | Fall 2013 | Fall 2011

    News:
  • I organize a graduate Certificate in Big Data; see stories from the U, the Salt Lake Tribune, and the Daily Utah Chronicle.
  • I have started posting videos of my lectures on my Youtube Channels.
  • I occasionally post on Geomblog including my experience in search for academic and research lab jobs.
  • I co-organized (with Suresh) an Algorithms in the Field-Computational Geometry (8F-CG) workshop during CG:APT at the Symposium on Computational Geoemtry in June 2012. Slides are now available.
    Publications:
  • Continuous Matrix Approximation on Distributed Data (to appear).
         Mina Ghashami, Jeff M. Phillips, and Feifei Li. 40th International Conference on Very Large Data Bases (VLDB). September 2014.

  • Relative Errors for Deterministic Low-Rank Matrix Approximations.
         Mina Ghashami and Jeff M. Phillips. 25th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA). January 2014.
         arXiv:1307.7454. June 2013.

  • Quality and Efficiency for Kernel Density Estimates in Large Data.
         Yan Zheng, Jeffrey Jestes, Jeff M. Phillips, Feifei Li. ACM Conference on the Management of Data (SIGMOD). June 2013.
         Project Page

  • Nearest Neighbor Searching Under Uncertainty II.
         Pankaj K. Agarwal, Boris Aronov, Sariel Har-Peled, Jeff M. Phillips, Ke Yi, and Wuzhou Zhang. 32nd ACM Symposium on Principles of Database Systems (PoDS). June 2013.

  • Range Counting Coresets for Uncertain Data.
         Amirali Abdullah, Samira Daruki, and Jeff M. Phillips. 29th Annual ACM Symposium on Computational Geometry (SoCG). June 2013.
         arXiv:1304.4243. April 2013.

  • Radio Tomographic Imaging and Tracking of Stationary and Moving People via Kernel Distance.
         Yang Zhao, Neal Patwari, Jeff M. Phillips, and Suresh Venkatasubramanian. 12th ACM-IEEE Conference on Information Processing in Sensor Networks (IPSN). April 2013.

  • eps-Samples for Kernels.
         Jeff M. Phillips. 24th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA). January 2013.
         arXiv:1112.4105. April 2012.

  • Sensor Network Localization for Moving Sensors.
         Arvind Agarwal, Hal Daume III, Jeff M. Phillips, and Suresh Venkatasubramanian. 2nd IEEE ICDM International Workshop on Data Mining in Networks (DaMNet). December 2012.

  • Efficient Protocols for Distributed Classification and Optimization.
         Hal Daume III, Jeff M. Phillips, Avishek Saha, and Suresh Venkatasubramanian. 23rd International Conference on Algorithmic Learning Theory (ALT). October 2012.
         arXiv:1204.3523. April 2012.
         See also a similar independent work: arXiv:1204.3514 (on arXiv same day)

  • Ranking Large Temporal Data.
         Jeffrey Jestes, Jeff M. Phillips, Feifei Li, and Mingwang Tang. 38th International Conference on Very Large Databases (VLDB). August 2012.
         PVLDB 5:1412-1423, 2012.
         arXiv:1208.0222 August 2012.
         Project Page

  • Mergeable Summaries.
         Pankaj K. Agarwal, Graham Cormode, Zengfeng Huang, Jeff M. Phillips, Zhewei Wei, and Ke Yi. 31st ACM Symposium on Principals of Database Systems (PODS). May 2012.
         ACM Transactions on Database Systems (TODS) 38:26, 2013.
         appeared as "Mergeable Coresets" in Third Workshop on Massive Data Algorithmics. June 2011.

  • Protocols for Learning Classifiers on Distributed Data.
         Hal Daume III, Jeff M. Phillips, Avishek Saha, and Suresh Venkatasubramanian. 15th Interntational Conference on Artificial Intelligence and Statistics (AISTATS). April 2012.
         full version as arXiv:1202.6078. February 2012.

  • Efficient Threshold Monitoring for Distributed Probabilistic Data.
         Mingwang Tang, Feifei Li, Jeff M. Phillips, Jeffrey Jestes. 28th IEEE International Conference on Data Engineering (ICDE). April 2012.

  • Uncertainty Visualization in HARDI based on Ensembles of ODFs.
         Fangxiang Jiao, Jeff M. Phillips, Yaniv Gur, and Chris R. Johnson. 5th IEEE Pacific Visualization Symposium (PacificVis). February 2012.

  • Lower Bounds for Number-in-Hand Multiparty Communication Complexity, Made Easy.
         Jeff M. Phillips, Elad Verbin, Qin Zhang. 23rd Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA). January 2012.
         arXiv:1107.2559. July 2011.

  • Generating A Diverse Set Of High-Quality Clusterings. (Best-Paper-Award)
         Jeff M. Phillips, Parasaran Raman, Suresh Venkatasubramanian. 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings (MultiClust). September 2011.
         arXiv:1108.0017. August 2011.

  • Geometric Computation on Indecisive Points.
         Allan G. Jorgensen, Maarten Loffler, Jeff M. Phillips. 12th Algorithms and Data Structure Symposium (WADS). August 2011.
         long version as Geometric Computatations on Indecisive and Uncertain Points as arXiv:1205.0273. May 2012. (merged with this)

  • Horoball Hulls and Extents in Positive Definite Space.
         P. Thomas Fletcher, John Moeller, Jeff M. Phillips, Suresh Venkatasubramanian. 12th Algorithms and Data Structure Symposium (WADS). August 2011.
         older long version as arXiv:0912.1580. December 2009.

  • Comparing Distributions and Shapes Using the Kernel Distance.
         Sarang Joshi, Raj Varma Kommaraju, Jeff M. Phillips, Suresh Venkatasubramanian. 27th Annual Symposium on Computational Geometry (SoCG). June 2011.
         long version as arXiv:1001.0591. March 2011.

  • Spatially-Aware Comparison and Consensus for Clusterings.
         Jeff M. Phillips, Parasaran Raman, and Suresh Venkatasubramanian. 10th SIAM Intenational Conference on Data Mining (SDM). April 2011.
         arXiv:1102.0026. February 2011.

  • (Approximate) Uncertain Skylines.
         Peyman Afshani, Pankaj K. Agarwal, Lars Arge, Kasper Green Larsen, and Jeff M. Phillips. 14th International Conference on Database Theory (ICDT). March 2011.
         Theory of Computing Systems 52, 342--366 (Special Issue : ICDT 2011).

  • Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images.
         Fangxiang Jiao, Jeff M. Phillips, Jeroen Stinstra, Jens Krueger, Raj Varma Kummaraju, Edward Hsu, Julie Korenberg, Chris R. Johnson. 5th International Workshop on Medical Imaging and Augmented Reality (MIAR). September 2010.

  • Stability of epsilon-Kernels.
         Pankaj K. Agarwal, Jeff M. Phillips, Hai Yu. 18th Annual European Symposium on Algorithms (ESA). September 2010.
         long version as arXiv:1003.5874. March 2010.

  • Universal Multi-Dimensional Scaling.
         Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian. 16th Annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). August 2010.
         long version as arXiv:1003.0529. March 2010.
         related code.
         media: Data Mining Made Faster.

  • Incremental Multi-Dimensional Scaling.
         Arvind Agarwal, Jeff M. Phillips, Hal Daume III, Suresh Venkatasubramanian. The Learning Workshop at Snowbird. April 2010.

  • Lipschitz Unimodal and Isotonic Regression on Paths and Trees.
         Pankaj K. Agarwal, Jeff M. Phillips, Bardia Sadri. 9th Latin American Theoretical Informatics Symposium (LATIN). April 2010.
         long version as arXiv:0912.5182. December 2009.

  • Shape Fitting on Point Sets with Probability Distributions.
         Maarten Loffler, Jeff M. Phillips. 17th Annual European Symposium on Algorithms (ESA). September 2009.
         long version as Geometric Computatations on Indecisive and Uncertain Points as arXiv:1205.0273. May 2012. (merged with this)

  • An Efficient Algorithm for Euclidean 2-Center with Outliers.
         Pankaj K. Agarwal, Jeff M. Phillips. 16th Annual European Symposium on Algorithms (ESA). September 2008.
         long version as arXiv:0806.4326. September 2008.

  • Algorithms for epsilon-Approximations of Terrains. (Best Student Paper)
         Jeff M. Phillips. 35th International Colloquium on Automata, Languages, and Programming (ICALP). July 2008.
         long version as arXiv:0801.2793. May 2008.

  • Spatial Scan Statistics for Graph Clustering.
         Bei Wang, Jeff M. Phillips, Robert Schrieber, Dennis Wilkinson, Nina Mishra, Robert Tarjan. 8th SIAM Intenational Conference on Data Mining (SDM). April 2008.

  • Value-Based Notification Conditions in Large-Scale Publish/Subscribe Systems.
         Badrish Chandramouli, Jeff M. Phillips, Jun Yang. 33rd Intenational Conference on Very Large Data Bases (VLDB). September 2007.

  • Outlier Robust ICP for Minimizing Fractional RMSD.
         Jeff M. Phillips, Ran Liu, Carlo Tomasi. 6th International Conference on 3-D Digital Imaging and Modeling (3DIM). August 2007.
         long version as Duke University Technical Report CS-2006-05 and arXiv: cs.GR/0606098. May 2006.
         poster/abstract for 4th Eurographics Symposium on Geometry Processing (SGP). June 2006.

  • Segmenting Motifs in Protein-Protein Interface Surfaces.
         Jeff M. Phillips, Johannes Rudolph, Pankaj K. Agarwal. Proceedings of the 6th Workshop on Algorithms in Bioinformatics (WABI). September 2006.

  • Spatial Scan Statistics: Approximations and Performance Study.
         Deepak Agarwal, Andrew McGregor, Jeff M. Phillips, Suresh Venkatasubramanian, Zhengyuan Zhu. 12th Annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). August 2006.

  • On Bipartite Matching under the RMS Distance.
         Pankaj K. Agarwal, Jeff M. Phillips. 18th Canadian Conference on Computational Geometry (CCCG). August 2006.

  • The Hunting of the Bump: On Maximizing Statistical Discrepancy.
         Deepak Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian. 17th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA). January 2006.
         abstract for Fall Workshop on Computational Geometry. November 2005.

  • Guided Expansive Spaces Trees: A Search Strategy for Motion- and Cost-Constrained State Spaces.
         Jeff M. Phillips, Nazareth Bedrossian, and Lydia E. Kavraki. IEEE International Conference on Robotics and Automation (ICRA). April 2004.

  • Spacecraft Rendezvous and Docking with Real-Time, Randomized Optimization.
         Jeff M. Phillips, Lydia E. Kavraki, and Nazareth Bedrossian. AIAA Guidance, Navigation, and Control. August 2003.

  • Probabilistic Optimization Applied to Spacecraft Rendezvous and Docking.
         Jeff M. Phillips, Lydia E. Kavraki, and Nazareth Bedrossian. AAS/AIAA Space Flight Mechanics Meeting. February 2003.

  • Simulated Knot Tying.
         Jeff M. Phillips, Andrew M. Ladd, Lydia E. Kavraki. IEEE International Conference on Robotics and Automation (ICRA). May 2002.

    Manuscripts:
  • Johnson-Lindenstrauss Dimensionality Reduction on the Simplex.
         Rasmus J. Kyng, Jeff M. Phillips, and Suresh Venkatasubramanian. 20th Fall Workshop on Computational Geometry. October 2010.

  • A Gentle Introduction to the Kernel Distance.
         Jeff M. Phillips, Suresh Venkatasubramanian. arXiv:1103.1625. March 2011.

  • Chernoff-Hoeffding Inequality and Applications.
         Jeff M. Phillips. arXiv:1209.6396. February 2013.

  • Geometric Inference on Kernel Density Estimates.
         Jeff M. Phillips, Bei Wang, and Yan Zheng. arXiv:1307.7760. January 2014.
         appeared as Kernel Distance for Geometric Inference. Jeff M. Phillips and Bei Wang. 22nd Fall Workshop on Computational Geometry. October 2012.

  • Rethinking Abstractions for Big Data: Why, Where, How, and What.
         Mary Hall, Robert M. Kirby, Feifei Li, Miriah Meyer, Valerio Pascucci, Jeff M. Phillips, Rob Ricci, Jacobus Van der Merwe, Suresh Venkatasubramanian. University of Utah, School of Computing, Tech Report: UUCS-13-002. April 2013.
         arXiv:1306.3295. June 2013.

  • Small and Stable Descriptors of Distributions for Geometric Statistical Problems.
         Jeff M. Phillips. Ph.D. Thesis: Department of Computer Science, Duke University. January 2009.
    Breif History of Jeff:
    Born and raised in the suburbs of Milwaukee, Wisconsin by parents John and Geri Phillips. One sister, Michelle, now in Washington DC.
    Married Bei Wang in summer 2009. She posts fun activities on a blog. One son Stanley, born in 2013.
    Received undergraduate education at Rice University. Graduated with a BS in Computer Science and a BA in Mathematics in 2003. Former member of Jones Residential College. Former member of the Kavraki Lab with Lydia Kavraki.
    Interned at Draper Labs near NASA JSC with Nazareth Bedrossian in 2002.
    Interned at AT&T Research -- Shannon Labs with   Suresh Venkatasubramanian in 2005.
    Interned at Yahoo! Research with Michael Mahoney in 2007.
    Attended graduate school in the Duke Computer Science Department with advisor Pankaj K. Agarwal. Successfully defended my PhD thesis January 19, 2009.
    Served as Postdoctoral Associate in the Duke Computer Science Department with supervisor Pankaj K. Agarwal.
    Served as a CI Postdoctoral Fellow at the University of Utah with mentor Suresh Venkatasubramanian.
    As of Fall 2011 is an Assistant Professor in the School of Computing at the University of Utah.


    Some of this material is based upon work supported by the National Science Foundation under Grant # 0937060 to the Computing Research Association for the CIFellows Project.
    Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or the Computing Research Association.